ETW3420 Principles of Forecasting and Applications
Principles of Forecasting and Applications
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Topic 4 Post-Tutorial Activity
Instructions
• Perform and complete the following tasks before answering the Quiz questions on
• In this activity, you will examine the Malaysia unemployment numbers and perform
decomposition analysis to extract some useful insights.
• Download and import into R, the Excel file which reports the Malaysia unemploy-
ment numbers (in thousands) from January 2009 to December 2015. When import-
ing the data into R, please also add the following argument header = FALSE in the
read.csv() function. In this way, the first row of the data set will NOT be regarded
as headings/labels.
Question 1: Plot the series
Plot the data and determine if an additive or multiplicative decomposition is more appro-
Question 2: Decomposition
Perform a multiplicative classical decomposition on the data and obtain the decomposition
plot. Also, print the decomposition output and note the following:
• Trend-cycle values, and how it was calculated
• Seasonal indices for the months
Question 3: Seasonally adjusted data
(a) Obtain the seasonally adjusted unemployment numbers. Observe the first value.
(b) Plot a graph which superimposes the seasonally adjusted unemployment numbers with
the actual unemployment numbers.
Question 4: Decomposition and Forecasting
Use the stlf() function to produce a 24 month forecast for the unemployment numbers,
whereby a random walk with drift is used to produce forecasts of the seasonally adjusted
unemployment numbers which are then subsequently reseasonalized. Set s.window = 13 in
the stlf() function.
Note the forecasted value for Dec 2017.
Instructions
Question 1: Plot the series
Question 2: Decomposition
Question 3: Seasonally adjusted data
Question 4: Decomposition and Forecasting
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